Pulmonary fibrosis is an idiopathic interstitial lung disease with high mortality. The illness is characterized by abnormal intraparenchymal deposition of collagen, with focal accumulations of fibroblasts, myofibroblasts and young connective tissue that are found in unique locations within the affected lung. We propose that aberrant responses of fibroblasts to growth factor and cytokine signaling underlie the progression of disease, and may represent appropriate targets for therapy and markers of response. Using a combination of broadbased techniques, the gene expression patterns of lungs and fibroblasts from patients with pulmonary fibrosis and controls will be discerned using novel algorithms allowing analysis of many thousands of genes per sample. Expression not only of relevant gene products but also signals reflecting response to growth factors and cytokines will be measured in tissue microarrays, where a single protein will be examined in hundreds of tissue samples. The activation state of distinct lung cellular compartments, defined in a fashion not previously feasible in tissue samples from human disease, will be mapped in patients and controls. The secretion of distinct proteins that reflect fibroblast origin and response to stimulation will be pursued both in vitro, but also using bronchoalveolar lavage as a window on secretion by lung cells. New proteomic techniques to enhance throughput and reduce variation will allow elucidation of BAL-derived proteins that reflect disease behavior. The result will be a set of targets plausibly involved in excessive fibroblastic response to signals, and in vitro evidence as to the potential success of intervention strategies. New biomarkers reflecting prognosis, nosology, and response to therapy will be discerned, potentially improving the yield of new trials. The data should advance our ability to treat and monitor pulmonary fibrosis.